Apple Tree Yield Analysis Using Data Mining

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FMPMSA2017_384TrajerPiotrowska.pdf (460.41 KB)
Authors
Trajer, Jędrzej
Pietrzycka, Iwona
Piotrowska, Ewa
Golisz, Ewa
Date
2017-11
Journal Title
Journal ISSN
Volume Title
Publisher
Department of Machinery Exploitation and Management of Production Processes, University of Life Sciences in Lublin, Poland
License
Creative Commons License
Creative Commons Attribution-NonCommercial 3.0 Poland License
Abstract
The paper analyses an orcharding farm that specializes in apple trees production. Based on the data for the period of 2008-2014, the authors analysed the main factors that might have impact on apple yield. A computer system for assessment of apple trees cultivation efficiency that aids in making appropriate decisions allowing for obtaining the highest yield, was proposed. The system was developed using selected Data Mining techniques such as cluster analysis and Kohonen networks. The system may be useful for decision support in sustainable horticulture production, and thus contributes to the development of sustainable agriculture. Although its quality is acceptable it still requires improvement using a bigger dataset.
Description
Keywords
apple tree yielding    data mining    sustainable gardening production
Citation
Trajer J., Pietrzycka I., Piotrowska E., Golisz E. 2017. Apple Tree Yield Analysis Using Data Mining. [in:] Lorencowicz E. (ed.), Uziak J. (ed.), Huyghebaert B. (ed.). Farm Machinery and Processes Management in Sustainable Agriculture, 9th International Scientific Symposium. ULS Lublin, p.384-388
URI
https://depot.ceon.pl/handle/123456789/14766
Belongs to collection
Sympozjum FMPMSA / FMPMSA Symposium
Materiały konferencyjne / Conference papers